Abstract
The paper proposes a new method for the optimized design of grid-connected Hybrid Solar Wind Power Systems (HSWPS). The optimization objectives are maximization of the economic efficiency and performance of the system. Evaluation of the objectives, related to assessment of the long-term performance of the system, is performed by means of a probabilistic model. Two different stochastic algorithms proved to be suitable for the optimization: Particle Swarm Optimization and Genetic Algorithms. The proposed strategy was applied to real systems, obtaining good solutions at low computational costs.
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